As more and more business, governmental, academic, and scientific operations become increasingly computer-enabled and, thus, dependent on the storage and manipulation of electronic or digital information, a greater need arises for efficient mechanisms for converting “physical” information into electronic or digital information capable of storage and manipulation by computers.
“Physical” information may include essentially any kind of information that is stored primarily in tangible, physical form, such as on paper, and is not readily available in electronic or digital form, but must instead be converted or translated into electronic or digital form through the use of electronic devices and/or manual human data-entry. For example, a utility bill printed on a piece paper received by a customer may be a form of “physical” information. Although the information printed on the utility bill may already exist in electronic or digital form—for example, in a commercial database operated by the utility company—that electronic information may not be available to the customer. Instead, if the customer wishes to store or manipulate the information printed on the paper document using a computer, he or she must either manually enter the information into a computer program or use a device, such as a scanner, that is designed to convert physical information into electronic or digital information.
Although the scanner in the above the example may effectively convert physical information to electronic information by generating a digital image of the scanned paper, because the printed bill would likely have not been formatted in a manner tailored to machine scanning and information extraction, the data captured from scanning the paper may include significant unnecessary graphical data or “noise.” Or, the scanner may not accurately read various characters, depending on the size of the font or the resolution of the scan. One solution that has been developed to address the need for efficiently and accurately converting physical information to electronic or digital information is the barcode.
A barcode is an optical, machine-readable image in which the information sought to be communicated by the barcode is arranged as a series of parallel lines of varying widths and spacings. Barcodes are typically scanned in a one-dimensional fashion by special-purpose optical scanning devices that are able to decode the information encoded in the barcodes by measuring the widths and spacings of the parallel barcode lines through reflective light feedback.
Traditional barcodes, however, suffer from the drawback that their one-dimensional structure allows for only a limited amount of information to be encoded in the barcode. For example, a Universal Product Code (UPC), which is a one-dimensional barcode format that enjoys widespread usage today, is capable of encoding only 12 decimal digits or a total of 95 binary bits, including start and end patterns. Because of this limitation, the last couple decades have seen significant growth in the number of standards for two-dimensional or “matrix” barcodes.
Many matrix barcodes provide similar functionality of traditional one-dimensional barcodes by providing a pattern of two-dimensionally arranged squares or other shapes of varying lengths and widths. One example of a type of matrix barcode that has enjoyed popular usage is the Quick Response or “QR” Code standard, an example of which is depicted in FIG. 1. Governed by several standards, QR Codes are capable of storing up to 7,089 decimal numeric code characters, 4,296 ASCII alphanumeric characters, or 2,953 bytes when encoding purely binary data.
Although by no means a new standard, QR Codes have recently gained widespread use as a result of the advancement of mobile devices, such as smartphones, capable of reading and quickly interpreting barcode data such as QR Codes. One common use of QR Codes, as depicted in FIG. 1, has been to encode Uniform Resource Locators (“URLs”), such as website addresses, within QR Codes placed on billboards, mailers, or even buildings to provide consumers with a quick and easy way to visit a company's website without having to memorize, write down, or manually type a URL into a smartphone or other mobile device. Consumers who see a QR Code displayed may take a picture of the QR Code using a camera embedded in the smartphone, for example, and may utilize a smartphone application to automatically translate the QR Code to a URL and launch a browser application pointed to the URL. Additional commercial uses of QR Codes include encoding coupons or other purchase information into QR Codes that customers may decode into graphical or textual coupons to present at businesses to receive discounts on purchased goods or services.
However, as the use of QR codes and other matrix barcodes becomes more widespread, a problem has emerged as the type and sophistication of commercially available scanning devices varies greatly. It therefore becomes a challenge to determine what kind of information to encode in barcodes that will be readable and actionable for the largest number of user scanning devices. Whereas an increasing number of mobile devices may be capable of scanning and decoding barcodes, those mobile devices may vary greatly in terms of which actions they may be capable of taking in response to decoded barcodes.
For example, an author of a barcode may choose to encode a URL in a barcode, such as a URL that points to a webpage containing information about the author's products. However, not all scanning devices capable of decoding the barcode may have web browsing capabilities. Some mobile devices may be capable only of initiating standard telephone calls or sending SMS text messages. Or, a scanning device may have web browsing capabilities, but the smart phone user may not have a data plan that provides for web browsing. Some mobile devices may be SMS capable, but not MMS capable. Moreover, some mobile devices may have sophisticated scanning capabilities, such as the ability to decode barcodes that contain audio or video content and the ability to play such audio or video content, but have no ability to communicate with other devices, such as through wireless transmission or otherwise.
The author of a barcode who wishes to widely disseminate information is thus presented with a predicament. On the one hand, the author may choose to encode a form or type of data into a barcode that will provide users who scan the barcode with the best quality of information or data richness, such as a hyperlink to a webpage or a video clip, in order to accomplish the most effective marketing of the author's information. However, such an approach may greatly limit the extent to which the information can be disseminated to the general public, as many users may use scanning devices that are not capable of accessing or rendering such content. Therefore, on the other hand, the author may choose to encode information in a barcode using a lowest common denominator approach—i.e., by encoding data in the simplest form, such as plain text, that will pose the least technological challenge for the greatest number of scanning devices. However, this latter approach may greatly limit the effectiveness of a barcode marketing campaign, since many users may be denied richer forms of information that their scanning devices would be able to access or render.
Thus, there is a need for methods and systems for incorporating multiple, distinct data items of different types into a single barcode, such as a QR Code, that will allow different users to access different forms of information according to the capabilities of their scanning devices.